Cancer is a leading cause of death in the world. According to the World Health Organization (WHO), about 8.2 million people died because of cancer in 2012, 70% of whom were living in developing countries. The number of cancer cases is expected to rise from 14 million in 2012 to 22 million in the next two decades.
Screening is widely accepted as an effective strategy for early detection of cancer, which can increase the rate of successful treatment. However, false positive alarms are common in screening, leading to significant unnecessary costs and psychological burdens in such cases. One major instance is screening the breast cancer, which is the most fatal cancer among women, causing more than 500,000 deaths worldwide in 2012.
Breast cancer screening is usually performed via mammography and clinical breast examination. However, similarities between physical and mammographic symptoms of benign and malignant lesions result in many false positive alarms. In such cases, benign lesions are unnecessarily chosen for biopsy. The limitations of mammography have been mentioned by many investigators, including Gøtzsche and Nielsen “Screening for breast cancer with mammography,” Cochrane Database Syst. Rev. 2013; 6:CD001877, whose observations of 600,000 women screened by mammography during 10 years showed that for every 2000 women, one's life would be extended, 10 healthy women would be unnecessarily treated, and 200 women would suffer intense psychological stress due to false positive alarms. Such deficiencies have motivated research to develop more efficient screening strategies.
Palpation of suspicious tissues has long been practiced by physicians to differentiate malignant tumors from benign lesions. Although this technique is limited to size and depth of diagnosed lesions, palpation lies on a simple yet useful physical principle: malignant lesions are much “stiffer” than benign ones. The concept of stiffness is closely related to elasticity, which has been widely studied in physics, and is the basis of an emerging medical imaging modality called “elastography”. The aim of this method is to provide more detailed and practical description of stiffness and other mechanical properties of tissues, which are independent from anatomical properties extractable from conventional medical images. Clinical studies of elastography, such as the work by Garra, et al “Elastography of breast lesions: initial clinical results”, Radiology 1997; 202:79-86, showed promising results in differentiating benign from malignant lesions, not only by distinguishing the difference in stiffness, but also due to the larger appearance of malignant tissues in elastograms (i.e., elasticity images), which is believed to be the consequent of desmoplastic reaction around malignant tissues. Several tissues have been imaged by elastography, including breast, prostate, thyroid, pancreas, lymph nodes, liver, kidney, etc.
Elasticity is defined as the tendency of tissues to resume their original size and shape, after being deformed by an applied “stress” (i.e., force acting on unit area). Hence, elasticity imaging requires analyzing two data sets corresponding to the pre- and post-deformation states of tissues. The “displacement” of tissues is estimated by comparing the pre- and post-deformation data. Depending on the application, the desired elasticity parameters are extracted from the displacement map.
Theoretically, any imaging modality can be used for displacement estimation. But due to practical limitations for medical imaging, only ultrasound and magnetic resonance imaging (MRI) systems have been utilized for this purpose so far. Since ultrasound is much less costly than MRI and is capable of real-time imaging, ultrasound elastography is more frequent in clinical applications. Specifically, a very cost-efficient technique, called “freehand elastography” (or quasi-static elastography), can be implemented on ordinary ultrasound imaging systems without any major hardware modification. In this technique, tissues are gently compressed by the ultrasound transducer, with such a low velocity that static mechanics can be assumed. In some applications, natural compression sources such as arterial pulsation or patient breathing, are utilized instead of the transducer for tissue deformation. Ultrasonic RF signals are acquired as tissues are compressed, via the same transducer performing the compression. The displacement of tissues is estimated by comparing pre- and post-deformation RF echoes. By taking the spatial derivative of displacement, “strain” distribution is obtained, which is the ratio of change in the length of tissues (due to the applied stress) to their original length. The strain map is displayed in a grayscale or colored image. Stiffer regions compress less than softer ones. Hence, they exhibit lower strain values. In other words, strain maps illustrate a relative stiffness distribution of tissues. Usually, the strain is kept lower than a few percent, resulting in sufficiently small displacements to preserve the similarity between pre- and post-deformation echo signals.
The cost saving in freehand elastography comes at the expense of some limitations. First, strain should be almost uniform to interpret the image, which implies that the compression must be performed carefully. However, the tendency of objects for out-of-plane motion makes it difficult to perform such compression, especially for deeper organs that are less influenced by the applied stress. These limitations can greatly degrade the quality of strain maps. The majority of elasticity imaging systems in which strain maps are generated offline, resolve this issue by collecting several input RF frames to make sure that acceptable frames are obtained. However, this approach is too time-consuming for busy clinical practice. The alternative is real-time strain imaging, which provides instant feedback to the operator to facilitate obtaining higher quality images. This technique also enables side-by-side (or overlaid) display of strain and real-time ultrasonic B-scan images for easy assessment of observed structures. However, due to the fact that calculations are minimized in real-time processing, real-time algorithms may suffer from lack of quality and robustness as compared with offline strain imaging methods. More specifically, they are more vulnerable to “signal decorrelation”, which is defined as the lack of correlation between pre- and post-deformation signals, caused by increasing the applied stress.
A few real-time displacement estimation techniques have been proposed to overcome the decorrelation issue, which are mainly based on coarse-to-fine approaches and tracking strategies. For instance, an article by L. Chen, R. J. Housden, G. M. Treece, A. H. Gee, and R. W. Prager, entitled “A hybrid displacement estimation method for ultrasonic elasticity imaging,” IEEE Trans. Ultrason. Ferroelect. Freq. Contr., 57:866-882, 2010, which is incorporated by reference herein, proposed a multi-level approach where the precision of displacement estimation was gradually increased and the displacement map was spread from the most qualified regions to the other parts. However, the decorrelation issue at the first step of the algorithm could affect the entire displacement estimation process in this approach.
Another notable work is reported in an by article H. Rivaz, E. M. Boctor, M. A. Choti, and G. D. Hager, entitled “Real-time regularized ultrasound elastography,” IEEE Trans. Med. Imag., 30:928-945, 2011, which is incorporated by reference herein. Rivaz et al. proposed a regularized algorithm named “Analytical Minimization” (AM) which provided the displacement estimation with subsample precision for a “seed line” of the RF frame, and propagated the estimation through adjacent lines to other parts of the displacement map. Although the regularization enhances the robustness of the algorithm against signal decorrelation, this issue can still affect the accuracy of the results through the seed line, where inaccurate estimation would spread to the whole image.
There exists a need for a real-time strain imaging method and apparatus with appropriate imaging quality and robustness for ordinary clinical use, where the operator's concentration performing compression and data acquisition is not as high as that of laboratory conditions.
It is very desirable that the real-time strain imaging method and apparatus be developed in such a way to be independent of input data and imaging modality so that it can be utilized in any medical, industrial, or scientific application in which the study of elasticity is considered beneficial.